Technological novelty profile and invention's future impact

We consider inventions as novel combinations of existing technological capabilities. Patent data allow us to explicitly identify such combinatorial processes in invention activities. Unconsidered in the previous research, not every new combination is novel to the same extent. Some combinations are naturally anticipated based on patent activities in the past or mere random choices, and some appear to deviate exceptionally from existing invention pathways. We calculate a relative likelihood that each pair of classification codes is put together at random, and a deviation from the empirical observation so as to assess the overall novelty (or conventionality) that the patent brings forth at each year. An invention is considered as unconventional if a pair of codes therein is unlikely to be used together given the statistics in the past. Temporal evolution of the distribution indicates that the patenting activities become more conventional with occasional cross-over combinations. Our analyses show that patents introducing novelty on top of the conventional units would receive higher citations, and hence have higher impact.Comment: 20 pages, 7 figure

The motivation and status of two-body resonance decays after the LHC Run 2 and beyond

Searching for two-body resonance decays is a central component of the high energy physics energy frontier research program. While many of the possibilities are covered when the two bodies are Standard Model (SM) particles, there are still significant gaps. If one or both of the bodies are themselves non-SM particles, there is very little coverage from existing searches. We review the status of two-body searches and motivate the need to search for the missing combinations. It is likely that the search program of the future will be able to cover all possibilities with a combination of dedicated and model agnostic search approaches.Comment: 17 pages, 1 figure, 14 table

Fundamental Structural Constraint of Random Scale-Free Networks

We study the structural constraint of random scale-free networks that determines possible combinations of the degree exponent $\gamma$ and the upper cutoff $k_c$ in the thermodynamic limit. We employ the framework of graphicality transitions proposed by [Del Genio and co-workers, Phys. Rev. Lett. {\bf 107}, 178701 (2011)], while making it more rigorous and applicable to general values of kc. Using the graphicality criterion, we show that the upper cutoff must be lower than $k_c N^{1/\gamma}$ for $\gamma < 2$, whereas any upper cutoff is allowed for $\gamma > 2$. This result is also numerically verified by both the random and deterministic sampling of degree sequences.Comment: 5 pages, 4 figures (7 eps files), 2 tables; published versio

Measurements of nonlinear harmonic waves at cracked interfaces

Nonlinear harmonic waves generated at cracked interfaces are investigated both experimentally and theoretically. A compact tension specimen is fabricated and the amplitude of transmitted wave is analyzed as a function of position along the fatigued crack surface. In order to measure as many nonlinear harmonic components as possible a broadband Lithium Niobate (LiNbO3) transducers are employed together with a calibration technique for making absolute amplitude measurements with fluid‐coupled receiving transducers. Cracked interfaces are shown to generate high acoustic nonlinearities which are manifested as harmonics in the power spectrum of the received signal. The first subharmonic (f∕2) and the second harmonic (2f) waves are found to be dominant nonlinear components for an incident toneburst signal of frequency f. To explain the observed nonlinear behavior a partially closed crack is modeled by planar half interfaces that can account for crack parameters such as crack opening displacement and crack surface conditions. The simulation results show reasonable agreements with the experimental results

Modeling Differently Oriented Loblolly Pine Strands Incorporating Variation of Intraring Properties Using a Stochastic Finite Element Method

Wood strands are a biological material with variations in material properties because of the presence of earlywood and latewood, juvenile wood and mature wood as well as the sectional cut used to generate strands. This variation should be accounted for to produce reliable modeling results. This study used both a deterministic finite element method (FEM) and a stochastic finite element method (SFEM) to model the stiffness of wood strands from three different orientations (radial, tangential, and angled) incorporating intraring property variation from two growth ring positions. In addition, a homogeneous model was used as a control to compare the results from both deterministic FEM and SFEM. The homogeneous model predicted the stiffness well for radial and tangential orientation strands but provided unrealistic physical strain distributions. Assumptions of strand homogeneity oversimplified the strain distribution present in the strand, eliminating local maximum and minimum values. Cumulative probability curves comparing previous experimental results and SFEM results showed general agreement. Average differences in the effective tensile modulus of elasticity ranged 0.96-22.31%. Based on the modeling results, the earlywood tensile modulus of elasticity was the input parameter that had the greatest influence on the strand stiffness. The order of correlation of the earlywood and latewood Poisson ratios changed based on strand orientation. SFEM techniques provided accurate results and material property distributions as compared with the experimental results

Sensitivity of Different Types of Observations to NASA GEOS Hurricane Analyses and Forecasts

The 2017 Atlantic hurricane season was the 5th most active, featuring 17 named storms, the highest number of major hurricanes since 2005, and by far the costliest season on record. African easterly waves often serve as the seeding circulation for a large portion of hurricanes (i.e. tropical storms with wind over 74mph in the Atlantic and Northeast Pacific). Warm SST, moist air, and low wind shear are the main requirements for tropical cyclones to develop and maintain hurricane strength. In terms of hurricane propagation (so called hurricane tracks), Atlantic hurricanes typically propagate around the periphery of the subtropical ridge called the Bermuda High (Azores High), riding along its strongest winds. If the high is positioned to the east, then hurricanes generally propagate northeastward around the high's western edge into the open Atlantic Ocean without making land fall. If the high is positioned to the west and extends far enough to the south, storms are blocked from curving north and forced to continue west towards Florida, Cuba, and the Gulf of Mexico. If we have accurate atmospheric temperature distribution, which is directly related to atmospheric wave patterns, wind distributions, moisture distribution, and SST distribution in the analyses, we will have better NWP skills in hurricane analyses including hurricane intensity and tracks. Assimilating various observation data are supposed to play these roles in the analyses. To examine impacts of different types of observation data on NASA Goddard Earth Observing System (GEOS) model hurricane analyses and forecasts during the period of 2017 summer, this study performs data denial experiments using GEOS Atmospheric Data Assimilation System (ADAS), which is based on the hybrid 4D-EnVar GSI algorithm. Various types of observations such as microwave sounders, infrared sounders, TCvitals, and conventional data are removed in the experiments. In addition, the interaction between the different observation groups as certain instruments are removed from the analysis is investigated in detail using adjoint based forecast sensitivity observation impact (FSOI)